Globally, abundant agricultural wastes (AWs) are being generated each day to fulfil the increasing demands of the fast-growing population. The limited and/or improper management of the same has created an urgent need to devise strategies for their timely utilization and valorisation, for agricultural sustainability and human-food and health security. The AWs are generated from different sources including crop residue, agro-industries, livestock, and aquaculture. The main component of the crop residue and agro-industrial waste is cellulose, (the most abundant biopolymer), followed by lignin and hemicellulose (lignocellulosic biomass). The AWs and their processing are a global issue since its vast majority is currently burned or buried in soil, causing pollution of air, water and global warming. Traditionally, some crop residues have been used in combustion, animal fodder, roof thatching, composting, soil mulching, matchsticks and paper production. But lignocellulosic biomass can also serve as a sustainable source of biofuel (biodiesel, bioethanol, biogas, biohydrogen) and bioenergy in order to mitigate the fossil fuel shortage and climate change issues. Thus, valorisation of lignocellulosic residues has the potential to influence the bioeconomy by producing value-added products including biofertilizers, bio-bricks, bio-coal, bio-plastics, paper, biofuels, industrial enzymes, organic acids etc. This review encompasses circular bioeconomy based various AW management strategies, which involve 'reduction', 'reusing' and 'recycling' of AWs to boost sustainable agriculture and minimise environmental pollution.
Abstract The adoption of emerging technological trends and applications of the Internet of Things (IoT) in the industrial systems is leading towards the development of Industrial IoT (IIoT). IIoT serves as a new vision of IoT in the industrial sector by automating smart objects for sensing, collecting, processing and communicating the real-time events in industrial systems. The major objective of IIoT is to achieve high operational efficiency, increased productivity, and better management of industrial assets and processes through product customization, intelligent monitoring applications for production floor shops and machine health, and predictive and preventive maintenance of industrial equipment. In this paper, we present a new and clear definition of IIoT, which can help the readers to understand the concept of IIoT. We have described the state-of-the-art research efforts in IIoT. Finally, we have highlighted the enabling technologies for IIoT and recent challenges faced by IIoT.
Industrial Internet of Things (IIoT) plays an indispensable role for Industry 4.0, where people are committed to implement a general, scalable, and secure IIoT system to be adopted across various industries. However, existing IIoT systems are vulnerable to single point of failure and malicious attacks, which cannot provide stable services. Due to the resilience and security promise of blockchain, the idea of combining blockchain and Internet of Things (IoT) gains considerable interest. However, blockchains are power-intensive and low-throughput, which are not suitable for power-constrained IoT devices. To tackle these challenges, we present a blockchain system with credit-based consensus mechanism for IIoT. We propose a credit-based proof-of-work (PoW) mechanism for IoT devices, which can guarantee system security and transaction efficiency simultaneously. In order to protect sensitive data confidentiality, we design a data authority management method to regulate the access to sensor data. In addition, our system is built based on directed acyclic graph -structured blockchains, which is more efficient than the Satoshi-style blockchain in performance. We implement the system on Raspberry Pi, and conduct a case study for the smart factory. Extensive evaluation and analysis results demonstrate that credit-based PoW mechanism and data access control are secure and efficient in IIoT.
Industrial Internet of Things (IIoT) lays a new paradigm for the concept of Industry 4.0 and paves an insight for new industrial era. Nowadays smart machines and smart factories use machine learning/deep learning based models for incurring intelligence. However, storing and communicating the data to the cloud and end device leads to issues in preserving privacy. In order to address this issue, federated learning (FL) technology is implemented in IIoT by the researchers nowadays to provide safe, accurate, robust and unbiased models. Integrating FL in IIoT ensures that no local sensitive data is exchanged, as the distribution of learning models over the edge devices has become more common with FL. Therefore, only the encrypted notifications and parameters are communicated to the central server. In this paper, we provide a thorough overview on integrating FL with IIoT in terms of privacy, resource and data management. The survey starts by articulating IIoT characteristics and fundamentals of distributive and FL. The motivation behind integrating IIoT and FL for achieving data privacy preservation and on-device learning are summarized. Then we discuss the potential of using machine learning, deep learning and blockchain techniques for FL in secure IIoT. Further we analyze and summarize the ways to handle the heterogeneous and huge data. Comprehensive background on data and resource management are then presented, followed by applications of IIoT with FL in healthcare and automobile industry. Finally, we shed light on challenges, some possible solutions and potential directions for future research.
Purpose The purpose of this paper is to reveal the inner mechanisms of the role of industrial internet platforms in empowering the digital transformation of SMEs. This ROOTCLOUD-based case study shows that knowledge integration and knowledge sharing and driving play essential empowering roles in the impact of industrial internet platforms on the digital transformation of SMEs. The industrial internet platform promotes knowledge integration on the supply side, empowers cross-domain knowledge sharing and shapes the knowledge-driven digital supply chain system in the digital transformation processes of SMEs. Design/methodology/approach This paper presents a qualitative analysis of the knowledge empowerment role played by industrial internet platforms in the digital transformation process of SMEs. Based on theoretical sampling, this paper selects ROOTCLOUD as a typical case to analyse the implementation mechanism of the industrial internet platform in solving the digital transformation problems and challenges faced by SMEs. Findings Knowledge management (knowledge integration, sharing and driving) plays an important intermediary role between the empowerment of industrial internet platform and the digital transformation of SMEs. Specifically, the industrial internet platform empowers SMEs with knowledge, empowers supply-side knowledge integration, empowers cross-domain knowledge sharing and facilitates the formation of knowledge-driven supply chain systems. Research limitations/implications This study clarifies the mechanism underlying the digital transformation of SMEs empowered by industrial internet platforms, that is, the empowerment of industrial internet platform enhances the level of knowledge integration and sharing of SMEs, thus improving the effectiveness of SMEs in achieving digital transformation. Further empirical studies should be conducted on the above mechanism. Originality/value Based on the theoretical perspective of knowledge management, this paper discusses the problems and challenges faced in the digital transformation of SMEs through knowledge empowerment by the industrial internet platform ROOTCLOUD and proposes that knowledge empowerment in the industrial internet platform helps supply-side knowledge integration, promotes cross-domain knowledge sharing and contributes to forming a knowledge-driven supply chain system, thereby promoting the digital transformation of SMEs. System architects and relevant policy departments should pay attention to data-centred system construction, improve the construction of data-based collaborative application ecology and encourage industrial internet platforms to provide more targeted knowledge empowerment solutions for SMEs.
To conceptualize living systems based on the processes that create them, rather than their interactions with the environment, as in systems theory. Maturana and Varela (1969) at the University of Chile introduced the term autopoiesis (from Greek self and production). This concept emphasizes autonomy as the defining feature of living systems. It describes them as self-sustaining entities that preserve their identity through continuous self-renewal to preserve their unity. Furthermore, these systems can only be understood in reference to themselves, as all internal activities are inherently self-determined by self-production and self-referentiality. This thesis introduces the Fuzzy Autopoietic Knowledge Management (FAKM) model, which integrates the system theory of living systems, the cybernetic theory of viable systems, and the autopoiesis theory of autopoietic systems. The goal is to move beyond traditional knowledge management models that rely on Cartesian dualism (cognition/action) where knowledge is treated as symbolic information processing. Instead, the FAKM model adopts a dualism of organization/structure to define an autopoietic system within a sociotechnical approach. The model is experimentally applied to a manufacturing company in the Maule Region, south of Santiago, Chile.
Home healthcare has become more and more central in the last decades, due to the advantages it can bring to both healthcare institutions and patients. Planning activities in this context, however, presents significant challenges related to route planning and mutual synchronization of caregivers.In this paper we propose a new compact model for the combined optimization of scheduling (of the activities) and routing (of the caregivers) characterized by fewer variables and constraints when compared with the models previously available in the literature. The new model is solved by a constraint programming solver and compared experimentally with the exact and metaheuristic approaches available in the literature on the common datasets adopted by the community. The results show that the new model provides improved lower bounds for the vast majority of the instances, while producing at the same time high quality heuristic solutions, comparable to those of tailored metaheuristics, for small/medium size instances.
Zhengguo Sheng, Chinmaya Mahapatra, Chunsheng Zhu
et al.
With the accelerated development of Internet-of-Things (IoT), wireless sensor networks (WSNs) are gaining importance in the continued advancement of information and communication technologies, and have been connected and integrated with the Internet in vast industrial applications. However, given the fact that most wireless sensor devices are resource constrained and operate on batteries, the communication overhead and power consumption are therefore important issues for WSNs design. In order to efficiently manage these wireless sensor devices in a unified manner, the industrial authorities should be able to provide a network infrastructure supporting various WSN applications and services that facilitate the management of sensor-equipped real-world entities. This paper presents an overview of industrial ecosystem, technical architecture, industrial device management standards, and our latest research activity in developing a WSN management system. The key approach to enable efficient and reliable management of WSN within such an infrastructure is a cross-layer design of lightweight and cloud-based RESTful Web service.
Bulbul Ahamed, Mohammad Rashed Hasan Polas, Ahmed Imran Kabir
et al.
The purpose of the study is to examine how cybersecurity knowledge, password security, and self-perception of skill affect cybersecurity awareness issues via the mediating lens of cybersecurity attitude among university students in Bangladesh. A sample of 430 university students from two public and three private universities provided the data in Dhaka, Bangladesh. An approach known as stratified random sampling was used in this cross-sectional study. The positivist approach was used, and a hypothetical statistical induction technique was used. The research constructs, which were adopted from earlier studies, were measured using scales that had undergone validation. Smart PLS-SEM 3.3.9 was used to quantitatively analyze the data. The results indicated a positive and significant association between cybersecurity knowledge and password security with cybersecurity awareness. No conventional association was found between self-perception of skills and cybersecurity awareness. Moreover, the data analysis confirmed that cybersecurity attitudemediates the relationship between cybersecurity knowledge, password security and self-perception of skills with cybersecurity awareness. This study implies that more effort needs to be put into informing the general people likely students about cybersecurity and ethical internet use. Furthermore, the main contribution of this study is to emphasize the need of raising cybersecurity awareness among students.
History of scholarship and learning. The humanities, Social Sciences
Change management is a complex process by which organisations adapt to new market conditions, technologies, regulations or consumer needs. In the context of trade SMEs, changes can have a significant impact on long-term competitiveness and sustainability. This paper aims to analyse the management of change in trade SMEs, carrying out a comparative study between retail and traditional trade.
LIN Qinbao(林勤保), YANG Qinghua(杨青华), ZHAO Dan(赵丹)
et al.
Per- and polyfluoroalkyl substances (PFASs) were a class of synthetic chemicals widely used in industrial products and consumer products. Due to their structural diversity and bioaccumulation properties, PFASs were recognized as highly concerned persistent pollutants. PFASs in food contact paper could contaminate food and endanger consumer health. There were various categories of PFASs, usually divided into polymers and non-polymers categories. Non-polymeric PFASs included perfluoroalkyl acids (PFAAs) and their precursors, while polymeric PFASs were mainly perfluoropolyethers (PFPEs) and fluoropolymers polymerized by multiple PFASs. According to the number of carbon atoms in the fluorine segment structure, PFASs were divided into long-chain PFASs with more than 7 carbon atoms and short-chain PFASs. Among them, common perfluorooctane sulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) were long-chain PFAAs, which were the key substances in research and regulatory supervision. In food contact paper, PFASs came from a wide range of sources, which were not only intentionally added through impregnation, sizing, or coating to improve the performance of paper products but also unintentional addition caused by manufacturing process residues or external environmental pollution. Pollution was common in various types of paper products. Although some traditional PFASs were under control, new PFASs and their precursors were still being detected, and the degree of pollution in different countries and regions was affected by regulatory efforts. In terms of dietary exposure, PFASs in food contact paper could migrate to food and enter the human body through dietary intake. Migration was affected by temperature, time, and food properties. The risks of using fast food paper at high temperatures should be closely monitored.Many countries and regions have implemented controls on PFASs, with different limit requirements. China also prohibited the production, processing, and use of some PFASs and adopted forward inventory management. Detection technologies included quantitative analysis of targeted PFASs, fluorine content screening, and non-targeted analysis of unknown PFASs. In the future, research on PFASs in food contact paper should focus on comprehensive assessment, combining multiple analytical methods, and tracing the source, distribution and toxicity hazards of unknown PFASs to improve regulatory regulations.(全氟或多氟烷基化合物(per- and polyfluoroalkyl substances, PFASs)是一类广泛应用于工业制品和消费品中的合成化学物质。由于其具有结构多样性和生物蓄积特性,PFASs被认定为高度关注的持久性污染物。食品接触用纸中的PFASs可能会污染食品,并危害到消费者的健康。PFASs种类多样,通常可分为聚合物和非聚合物两类,非聚合类PFASs包括全氟烷基酸(perfluoroalkyl acids, PFAAs)及其前体物,聚合物PFASs主要是全氟聚醚(perfluoropolyethers, PFPEs)和由多个PFASs聚合而成的含氟聚合物；按氟链段结构中碳原子数,PFASs分为碳原子数量大于7个的长链PFASs和短链PFASs,其中常见的全氟辛烷磺酸(perfluorooctane sulfonic acid, PFOS)、全氟辛酸(perfluorooctanoic acid, PFOA)是长链PFAAs,是研究和法规监管中重点关注的物质。在食品接触用纸中,PFASs 来源广泛,既通过浸渍、施胶或涂层等方式有意添加以提升纸制品性能,也有制造过程残留或外部环境污染导致的非有意添加情况。污染情况在各类纸制品中普遍存在,尽管部分传统 PFASs 受管控,但新型PFASs及其前体物仍不断被检出,且不同国家或地区污染程度受监管力度影响。在膳食暴露方面,食品接触用纸中的 PFASs 可迁移至食品,经饮食摄入进入人体,迁移受温度、时间、食品性质影响,快餐类用纸在高温下使用时的风险需重点关注。多个国家和地区已对 PFASs 实施管控,限量要求各有不同,我国也禁止部分 PFASs 的生产加工使用并采用正向清单管理。检测技术包括靶向 PFASs 定量分析、氟含量筛查及未知 PFASs 非靶向分析。未来食品接触用纸中 PFASs 研究应更注重全面评估,结合多种分析方法,并追溯未知 PFASs 来源、分布与毒性危害,以完善监管法规。)
In this paper, a particular form of practical ℎ-observers for piecewise continuous Lipschitz, one-sided piecewise continuous Lipschitz systems and quasi-one-sided piecewise continuous Lipschitz systems is extended to nonlinear non-autonomous dynamical systems with disturbances. With the notion of practical ℎ-stable functions, the obtained state estimates are used for an eventual feedback control, and the practical separation principle is tackled. An example is given to show the applicability of the main result.